Snigdha Kakkar's Projects
A scalable API for names and contests created using GraphQL and javascript for coding
Algorithms for practice
An Audio Classification Project Using ML & DL on Urbansound8K Dataset (Kaggle): Sound Classification using Librosa, MFCC, CNN, Keras, XGBOOST, Random Forest.
Automobile Mileage Prediction using Multiple Regression Models in Machine Learning (Scikit-learn Python Library)
A music app using Swing (Java)
A simple chat application using Java and various Java API libraries.
Exercises for learning basic python
Developed an application for tracking Covid cases using python. Also performed Exploratory data analysis to understand more about the data coming in and deduced patterns. Used Papermill to schedule the automatic run of the jupyter notebook. The details on how to install and run papermill are mentioned in the Jupyter notebook itself.
COVID-19-Confirmed, Death and Recovered Case Predictions for US (As a part of Assignments in Data And Knowledge Management Course at University of Waterloo)
TensorFlow Object Detection
Shopify DS Challenge
Predicting exam scores for children using regression model on various attributes
Devised a Face Recognition App Using: 1. Flask Web Framework 2. Haarcascades xml files for facial features 3. CSS Stylesheet 4. OpenCV, Numpy, FaceRecognition, Render_template, Response, Url_for Modules from Python 5. Python language for coding
Implemented Transfer Learning using State Of Art Models of CNN (Vgg16, Resnet)
Implementing Fake news Classifier Using LSTM
Convolutional Neural Network Implementation and Optimization Using Keras_tuner in Google Colab
Hands On Practice Code in addition to Generative AI YouTube Playlist for learners
heart disease detection using K Nearest Neighbor (KNN) algorithm
Applications of People Analytics in Hiring and Recruiting Vendors' optimization
Steps Implemented: 79 initial features Technologies: Python, NLTK, Keras, Scikit-learn, pandas, Numpy Pre-processed the raw data, handled the missing values and applied feature engineering Used hyperparameter optimization techniques to find the optimum parameters Predicted Sale Prices to minimize the Cost function using Machine learning Regression models & Neural Networks Explored Linear regression with regularization methods (Ridge, LASSO etc.) & XgBoost Model using scikit-learn
Kaggle dataset 'California Housing' Analysis - Machine Learning Predictor using Scikit-learn
Image Classification Model Using Logistic Regression Model. Image data used is FashionMNIST.
Image classification Model Using Vgg19 (Transfer Learning) and implementing it on Flask web framework
Analysis of various factors to gauge the impact of COVID-19 on the North American Economy. Tools used: Tableau, SQL, REST API's and Secondary Research
Using Python libraries to predict Titanic survival rate
Implementing English to French Language translation using Machine Learning
Machine Learning Algo Implementation Python for Interviews
Attendance App Based on Face Recognition Tools used - Flask Web Framework Haarcascades xml files for facial features CSS OpenCV, Numpy, FaceRecognition, Render_template, Response, Url_for Modules from Python Python language for coding